Research On Sidelobe Suppression For Polyphase Complementary Frank Codes Through The Non-Ideal System

Sidelobe suppression has been a key issue during processing of the phase encoding signals. The range sidelobes have little impact on detecting ability under the single target's circumstances. If the number of targets increases, especially when the intensity of echoes from targets at different range cell varies greatly, the weak echoes may be completely covered by the range sidelobes of strong echoes. Complementary phase-coded signals have found widespread use in radar systems utilizing pulse compression technique due to their unique autocorrelation properties. However in actual application, nonzero sidelobe values appear when the complementary signals pass through the system with limited bandwidth which is used to suppress noise and filter interference signals. The non-ideal of the system leads to the disappearance of the complementary characteristics of the signal. After pulse compression the non-zero sidelobes appear. This paper gives a detailed discussion on sidelobe elevation of the polyphase complementary Frank codes.First this paper gives contrast of the biphase codes and the polyphase codes. Polyphase codes have more flexibility on choice and can obtain better autocorrelation characteristic. It gives detailed discussion of the complementary Frank codes and gives contrast of the complementary codes formed by the segment and by cycle shifting. And pointed out that segment polyphase complementary codes have better characteristic. At last it gives the signal structure of the polyphase complementary Frank codes.Second this paper builds the processing model of the polyphase complementary Frank codes, and gives the theoretical derivation of the result of the pulse compression. It points out sampling frequency and the choosed filter have the relationship to the result. By selecting the proper parameters, it can obtain the least peak sidelobe level (PSL). By simulation, the sampling frequency and the filter parameters are optimized choosed and makes the sidelobe down to -50dB.At last this paper gives the analysis and the discussion of the distortion of the signals passing through the FIR digital filter. Based on this, this paper uses two methods to suppress the sidelobe, that are the time-domain signal compensation algorithm based on the objectives and reconstruction reducing algorithm in time-domain. It gives detailed analysis of two algorithms, also gets the simulation results. This paper gives detailed discussion of the performance of two algorithms. It analyses the impact of the noise and the doppler frequency, and discusses the impact of the SNR by two algorithms. It can increase the dynamic detection performance by applying two algorithms, also can get better performance.